Any idea what could be causing this error? I've been trying to solve this for a week. Thanks in advance
main program is:
import pandas as pd
from sklearn.tree import DecisionTreeClassifier
music = pd.read_csv('sun1.csv')
X = music.drop(columns=['genre'])
y= music['genre']

model = DecisionTreeClassifier()
model.fit(X, y)
predictions=model.predict([ [21,1], [22, 0] ])
predictions

ValueError Traceback (most recent call last)
in
6
7 model = DecisionTreeClassifier()
----> 8 model.fit(X, y)
9 time.sleep(0.1)
10 predictions=model.predict([ [21,1], [22, 0] ])

C:\ProgramData\Anaconda3\lib\site-packages\sklearn\tree_classes.py in fit(self, X, y, sample_weight, check_input, X_idx_sorted)
875 sample_weight=sample_weight,
876 check_input=check_input,
--> 877 X_idx_sorted=X_idx_sorted)
878 return self
879

C:\ProgramData\Anaconda3\lib\site-packages\sklearn\tree_classes.py in fit(self, X, y, sample_weight, check_input, X_idx_sorted)
147
148 if check_input:
--> 149 X = check_array(X, dtype=DTYPE, accept_sparse="csc")
150 y = check_array(y, ensure_2d=False, dtype=None)
151 if issparse(X):

C:\ProgramData\Anaconda3\lib\site-packages\sklearn\utils\validation.py in check_array(array, accept_sparse, accept_large_sparse, dtype, order, copy, force_all_finite, ensure_2d, allow_nd, ensure_min_samples, ensure_min_features, warn_on_dtype, estimator)
576 if force_all_finite:
577 _assert_all_finite(array,
--> 578 allow_nan=force_all_finite == 'allow-nan')
579
580 if ensure_min_samples > 0:

C:\ProgramData\Anaconda3\lib\site-packages\sklearn\utils\validation.py in _assert_all_finite(X, allow_nan, msg_dtype)
58 msg_err.format
59 (type_err,
---> 60 msg_dtype if msg_dtype is not None else X.dtype)
61 )
62 # for object dtype data, we only check for NaNs (GH-13254)

ValueError: Input contains NaN, infinity or a value too large for dtype('float32').